论文标题
部分可观测时空混沌系统的无模型预测
Feasibility and Acceptability of Remote Neuromotor Rehabilitation Interactions Using Social Robot Augmented Telepresence: A Case Study
论文作者
论文摘要
储层计算是预测湍流的有力工具，其简单的架构具有处理大型系统的计算效率。然而，其实现通常需要完整的状态向量测量和系统非线性知识。我们使用非线性投影函数将系统测量扩展到高维空间，然后将其输入到储层中以获得预测。我们展示了这种储层计算网络在时空混沌系统上的应用，该系统模拟了湍流的若干特征。我们表明，使用径向基函数作为非线性投影器，即使只有部分观测并且不知道控制方程，也能稳健地捕捉复杂的系统非线性。最后，我们表明，当测量稀疏、不完整且带有噪声，甚至控制方程变得不准确时，我们的网络仍然可以产生相当准确的预测，从而为实际湍流系统的无模型预测铺平了道路。
There is a growing need to deliver rehabilitation care to patients remotely. Long term demographic changes, geographic shortages of care providers, and now a global pandemic contribute to this need. Telepresence provides an option for delivering this care. However, telepresence using video and audio alone does not provide an interaction of the same quality as in-person. To bridge this gap, we propose the use of social robot augmented telepresence (SRAT). We have constructed a demonstration SRAT system for upper extremity rehab, in which a humanoid, with a head, body, face, and arms, is attached to a mobile telepresence system, to collaborate with the patient and clinicians as an independent social entity. The humanoid can play games with the patient and demonstrate activities.These activities could be used both to perform assessments in support of self-directed rehab and to perform exercises. In this paper, we present a case series with six subjects who completed interactions with the robot, three subjects who have previously suffered a stroke and three pediatric subjects who are typically developing. Subjects performed a Simon Says activity and a target touch activity in person, using classical telepresence (CT), and using SRAT. Subjects were able to effectively work with the social robot guiding interactions and 5 of 6 rated SRAT better than CT. This study demonstrates the feasibility of SRAT and some of its benefits.
